class_docstr: TFRecord datasource, for reading and writing TFRecord files.
class_docstr_tok: ["TFRecord","datasource",",","for","reading","and","writing","TFRecord","files","."]
code: def __init__(
      self,
      paths: Union[str, List[str]],
      tf_schema: Optional["schema_pb2.Schema"] = None,
      **file_based_datasource_kwargs,
  ):
      super().__init__(paths, **file_based_datasource_kwargs)
  
      self.tf_schema = tf_schema
  
file_path: ray/python/ray/data/datasource/tfrecords_datasource.py
imports: import struct
  from typing import TYPE_CHECKING, Dict, Iterable, Iterator, List, Optional, Union
  import numpy
  from ray.data.block import Block
  from ray.data.datasource.file_based_datasource import FileBasedDatasource
  from ray.util.annotations import PublicAPI
label_desc: Use image node_id 1 to create a new TFRecordDatasource object from inherited base classes: FileBasedDatasource with example: obj = TFRecordDatasource(paths, tf_schema)